1. Field of the Invention
The invention relates to a method of analyzing information, more particularly to a method of qualitatively and quantitatively analyzing a diffusion-weighted magnetic resonance image.
2. Description of the Related Art
Magnetic resonance imaging (MRI) is a non-invasive imaging method for examining organs and tissues of the human body. It works on the principle that magnetic fields can change the direction of magnetic spin of hydrogen atoms in a living body, and excite resonance of hydrogen atom nuclei, and it uses a computer to analyze electromagnetic signals to create images. Since about 70% of the human body is water (H2O), which contains a large amount of hydrogen atom nuclei, MRI has been widely applied to clinical imaging.
Diffusion-weighted MR images (hereinafter referred to as DWI), which are capable of revealing detailed structures of tissue fibers, are realized through applying magnetic gradient pulses and receiving signals responding to diffusion of water molecules. Since diffusion of water molecules in tissues is mainly influenced by tissue structures, diffusion characteristics of water molecules can be used to estimate detailed structures of tissue fibers.
To analyze DWI, diffusion tensor imaging (DTI) techniques utilizing tensor analysis have been developed. Living organs are composed of non-homogeneous tissues, where the diffusion of water molecules exhibits an anisotropic pattern. Conventional diffusion coefficients can hardly reflect the diffusion characteristics of the water molecules clearly. Generally, magnetic gradients are applied in six specific directions to construct six diffusion-weighted images, along with one null image (imaging without magnetic gradient), which are analyzed to thereby obtain a tensor matrix. In DTI, a symmetric three-dimensional tensor matrix is used to describe the diffusion strength, and a tissue structure is inferred and constructed through eigen analysis.
A current method of improvement, known as high angular resolution diffusion imaging (HARDI), is to apply magnetic gradients in more directions during sampling. However, for the cerebral tissues of a human brain, the nerve fibers are largely intertwined, and it is difficult to discern the orientations of the fibers at fiber intersections. This manifests the fact that better analysis results cannot be obtained due to insufficient degree of freedom of the DTI matrix.
By further calculating HARDI information, an orientation distribution function (ODF) of a fiber at any one point in space can be obtained. However, techniques for qualitative and quantitative analysis of ODF are required if the number and orientations of the fibers also need to be known.
A current technical accomplishment is primarily concerned with finding local maximum values in ODFs to serve as orientations of the fibers. However, for ODFs at fiber intersections, if an included angle between two intersecting fibers is relatively small or if there are less branching fibers, such a method cannot be used to clearly analyze less conspicuous fibers. Therefore, with respect to qualitative and quantitative techniques for analyzing ODFs, further researches and developments are required.